'''simple docstring'''




from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader




class        a__ (  UpperCAmelCase__					):






     def __init__(					self						:						str    ,							a						:						pyspark.sql.DataFrame    ,							a						:						Optional[NamedSplit] = None    ,							a						:						Optional[Features] = None    ,							a						:						bool = True    ,							a						:						str = None    ,							a						:						bool = False    ,							a						:						str = None    ,							a						:						bool = True    ,							a						:						str = "arrow"    ,							**a						:						Dict    ,							):





         """simple docstring"""



         super().__init__(
             split=a    ,							features=a    ,							cache_dir=a    ,							keep_in_memory=a    ,							streaming=a    ,							**a    ,							)
         __lowerCamelCase            =    load_from_cache_file
         __lowerCamelCase            =    file_format
         __lowerCamelCase            =    Spark(
             df=a    ,							features=a    ,							cache_dir=a    ,							working_dir=a    ,							**a    ,							)






     def   SCREAMING_SNAKE_CASE__  (					self						:						int       ):





         """simple docstring"""



         if self.streaming:
             return self.builder.as_streaming_dataset(split=self.split       )
         __lowerCamelCase            =    None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
         self.builder.download_and_prepare(
             download_mode=a    ,							file_format=self._file_format    ,							)
         return self.builder.as_dataset(split=self.split       )

'''simple docstring'''




import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD






def __lowerCAmelCase					(				UpperCamelCase__							)      ->       List[str]:
    def wrapper(*UpperCamelCase__							,    **UpperCamelCase__							):
        __lowerCamelCase            =    timeit.default_timer()
        __lowerCamelCase            =    func(*UpperCamelCase__							,    **UpperCamelCase__							)
        __lowerCamelCase            =    timeit.default_timer() - starttime
        return delta

    __lowerCamelCase            =    func.__name__

    return wrapper






def __lowerCAmelCase					(				UpperCamelCase__							,    UpperCamelCase__=1_00							,    UpperCamelCase__=None							)      ->       Dict:
    __lowerCamelCase            =    []
    __lowerCamelCase            =    seq_shapes or {}
    for i in range(UpperCamelCase__							):
        __lowerCamelCase            =    {}
        for col_id, (k, v) in enumerate(features.items()							):
            if isinstance(UpperCamelCase__							,    _ArrayXD							):
                __lowerCamelCase            =    np.random.rand(*v.shape							).astype(v.dtype							)
            elif isinstance(UpperCamelCase__							,    datasets.Value							):
                if v.dtype == "string":
                    __lowerCamelCase            =    '''The small grey turtle was surprisingly fast when challenged.'''
                else:
                    __lowerCamelCase            =    np.random.randint(10							,    size=1							).astype(v.dtype							).item()
            elif isinstance(UpperCamelCase__							,    datasets.Sequence							):
                while isinstance(UpperCamelCase__							,    datasets.Sequence							):
                    __lowerCamelCase            =    v.feature
                __lowerCamelCase            =    seq_shapes[k]
                __lowerCamelCase            =    np.random.rand(*UpperCamelCase__							).astype(v.dtype							)
            __lowerCamelCase            =    data

        dummy_data.append((i, example)							)

    return dummy_data






def __lowerCAmelCase					(				UpperCamelCase__							,    UpperCamelCase__							,    UpperCamelCase__=1_00							,    UpperCamelCase__=None							)      ->       Dict:
    __lowerCamelCase            =    generate_examples(UpperCamelCase__							,    num_examples=UpperCamelCase__							,    seq_shapes=UpperCamelCase__							)

    with ArrowWriter(features=UpperCamelCase__							,    path=UpperCamelCase__							) as writer:
        for key, record in dummy_data:
            __lowerCamelCase            =    features.encode_example(UpperCamelCase__							)
            writer.write(UpperCamelCase__							)

        __lowerCamelCase      ,    __lowerCamelCase            =    writer.finalize()

    if not num_final_examples == num_examples:
        raise ValueError(
            f"""Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."""							)

    __lowerCamelCase            =    datasets.Dataset.from_file(filename=UpperCamelCase__							,    info=datasets.DatasetInfo(features=UpperCamelCase__							)							)

    return dataset
